Agricultural and Biosystems Engineering Publications

Campus Units

Agricultural and Biosystems Engineering, Human Computer Interaction, Plant Sciences Institute

Document Type

Article

Publication Version

Published Version

Publication Date

2016

Journal or Book Title

IFAC-PapersOnLine

Volume

49

Issue

16

First Page

265

Last Page

270

DOI

10.1016/j.ifacol.2016.10.049

Abstract

Sorghum is known as a major potential feedstock for biofuel production. Being able to efficiently discover genetic control of many traits over a large number of genotypes, genome-wide association study (GWAS) has become a powerful tool for studying sorghum biomass yield components. However, automated high-throughput field-based plant phenotyping is now the bottleneck for scaling up such experiments. This paper presents an auto-guidance enabled utility tractor which navigates itself between crop rows with a predefined path while collecting stereo images of sorghum samples from both sides of the vehicle. Three levels of stereo camera heads were instrumented to capture images of plants up to 3 meters tall. The stereo images were processed offline to reconstruct 3D point clouds using Semi-Global Block Matching. A semi-automated software interface was developed to measure stem diameter due to the strict sampling strategy and the complexity of high-density crop canopy. An automated hedge-based feature extraction pipeline was proposed to quantify other variations in plant architecture traits such as plant height, leaf area index (LAI) and vegetation volume index (VVI). The stem diameter measured using the semiautomatic method showed high correlation (0.958) to hand measurement.

Comments

This article is published as Bao, Yin, and Lie Tang. "Field-based robotic phenotyping for sorghum biomass yield component traits characterization using stereo vision." IFAC-PapersOnLine 49, no. 16 (2016): 265-270. DOI: 10.1016/j.ifacol.2016.10.049. Posted with permission.

Access

Open

Copyright Owner

IFAC (International Federation of Automatic Control)

Language

en

File Format

application/pdf

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